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Quantitative analysis and EEG markers of KCNT 1 epilepsy of infancy with migrating focal seizures
Author(s) -
Kuchenbuch Mathieu,
Benquet Pascal,
Kaminska Anna,
Roubertie Agathe,
Carme Emilie,
Saint Martin Anne,
Hirsch Edouard,
Dubois Fanny,
Laroche Cécile,
Barcia Giulia,
Chemaly Nicole,
Milh Matthieu,
Villeneuve Nathalie,
Sauleau Paul,
Modolo Julien,
Wendling Fabrice,
Nabbout Rima
Publication year - 2019
Publication title -
epilepsia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.687
H-Index - 191
eISSN - 1528-1167
pISSN - 0013-9580
DOI - 10.1111/epi.14605
Subject(s) - ictal , epilepsy , electroencephalography , neuroscience , psychology , audiology , medicine
Summary Objective We aimed to characterize epilepsy of infancy with migrating focal seizures (EIMFS), a rare, severe early onset developmental epilepsy related to KCNT 1 mutation, and to define specific electroencephalography (EEG ) markers using EEG quantitative analysis. The ultimate goal would be to improve early diagnosis and to better understand seizure onset and propagation of EIMFS as compared to other early onset developmental epilepsy. Methods EEG of 7 EIMFS patients with KCNT 1 mutations (115 seizures) and 17 patients with other early onset epilepsies (30 seizures) was included in this study. After detection of seizure onset and termination, spatiotemporal characteristics were quantified. Seizure propagation dynamics were analyzed using chronograms and phase coherence. Results In patients with EIMFS , seizures started and were localized predominantly in temporal and occipital areas, and evolved with a stable frequency (4‐10 Hz). Inter‐ and intrahemispheric migrations were present in 60% of EIMFS seizures with high intraindividual reproducibility of temporospatial dynamics. Interhemispheric migrating seizures spread in 71% from temporal or occipital channels to the homologous contralateral ones, whereas intrahemispheric seizures involved mainly frontotemporal, temporal, and occipital channels. Causality links were present between ictal activities detected under different channels during migrating seizures. Finally, time delay index (based on delays between the different ictal onsets) and phase correlation index (based on coherence of ictal activities) allowed discrimination of EIMFS and non‐ EIMFS seizures with a specificity of 91.2% and a sensitivity of 84.4%. Significance We showed that the migrating pattern in EIMFS is not a random process, as suggested previously, and that it is a particular propagation pattern that follows the classical propagation pathways. It is notable that this study reveals specific EEG markers (time delay and phase correlation) accessible to visual evaluation, which will improve EIMFS diagnosis.